Xin*_*ing 5 memory connection parallel-processing r
我正在 R 中运行一些模拟,代码在不使用并行计算的情况下运行良好。但是,当我修改一行代码并尝试使用并行计算时,R 卡住了,并且每次都卡在不同的迭代时间。当 R 卡住时,我必须手动停止它运行,有时会有一些警告说
Warning messages:
1: closing unused connection 13 (<-localhost:11688)
2: closing unused connection 12 (<-localhost:11688)
3: closing unused connection 9 (<-localhost:11688)
4: closing unused connection 8 (<-localhost:11688)
5: closing unused connection 7 (<-localhost:11688)
6: closing unused connection 6 (<-localhost:11688)
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或者类似的东西
Warning message:
In .Internal(get(x, envir, mode, inherits)) :
closing unused connection 6 (<-localhost:11688)
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这是我的代码:
for (iter in 1:100){
*Simulate data matrix X and Y, and initial start Z0*
for (i in 1:100){
*Calculate input matrix Z based on Z0*
cl <- makeCluster(no_cores, type="FORK")
Z <-cbind(Z,unlist(parLapply(cl,
as.list(data.frame(t(Z))),
function(x) prob(x,X,Y))))
stopCluster(cl)
result <- rbind(result,Z)
result <- result[!duplicated(result),]
result <- result[order(-result[,dim(result)[2]]),][1:10,]
*Calculate a new Z0 based on Z*
}
}
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其中 prob 是一个函数,返回一个长度等于 Z 行数的向量。
由于代码在不使用并行计算的情况下运行良好,我相信问题出在并行计算上。我没有使用parLapply,而是在迭代中尝试了foreach:
cl <- makeCluster(no_cores, type="FORK")
Z <- cbind(Z,foreach(tmp=as.list(data.frame(t(Z))),
.combine = c) %dopar%
prob(tmp,X,Y))
stopCluster(cl)
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在 R 卡住并且我手动停止它运行后,我收到类似的警告:
Warning messages:
1: closing unused connection 13 (<-localhost:11688)
2: closing unused connection 12 (<-localhost:11688)
3: closing unused connection 9 (<-localhost:11688)
4: closing unused connection 8 (<-localhost:11688)
5: closing unused connection 7 (<-localhost:11688)
6: closing unused connection 6 (<-localhost:11688)
7: In doTryCatch(return(expr), name, parentenv, handler) :
restarting interrupted promise evaluation
8: In doTryCatch(return(expr), name, parentenv, handler) :
restarting interrupted promise evaluation
9: In doTryCatch(return(expr), name, parentenv, handler) :
restarting interrupted promise evaluation
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我使用 3 个内核进行并行计算 (no_cores=3),机器是 Macbook pro 2016。
有人可以帮我吗?谢谢!
帮助我了解更多。你在循环,i但我没有看到你在使用它?我错过了什么吗?
另外,我建议在您的循环之外启动您的集群。您有效地创建和停止集群 10,000 次。
我makeCluster在循环之外调用,然后在循环完成后停止它。
尝试这样的事情:
cl <- makeCluster(no_cores, type="FORK")
clusterExport(cl, 'Z') # need to export the variable to cluster?
for (iter in 1:100){
*Simulate data matrix X and Y, and initial start Z0*
for (i in 1:100){
*Calculate input matrix Z based on Z0*
Z <-cbind(Z,unlist(parLapply(cl,
as.list(data.frame(t(Z))),
function(x) prob(x,X,Y))))
result <- rbind(result,Z)
result <- result[!duplicated(result),]
result <- result[order(-result[,dim(result)[2]]),][1:10,]
*Calculate a new Z0*
}
}
stopCluster(cl)
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如果这不起作用,请告诉我。我会尽量帮忙的!
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